from transformers import pipeline | |
import gradio as gr | |
# Load model | |
classifier = pipeline("text-classification", model="your-username/octagon") | |
def predict(text): | |
return classifier(text) | |
iface = gr.Interface( | |
fn=predict, | |
inputs=gr.Textbox(lines=2, placeholder="Enter text here..."), | |
outputs="label", | |
title="Octagon Text Classification", | |
description="A demo for the Octagon model trained on IMDB reviews." | |
) | |
iface.launch() |